Semantic Layer Method Of Relational Knowledge Network Based On Link Feature Analysis

With the rapid development of the Internet, network has become a warehouse containing a large number of information resources. People share network information resources through browsing information or releasing information on the Web.However, there are some contradictions between the large-scale information resources and the cognitive ability of the users in the related knowledge network. It is difficult to provide the corresponding knowledge services when the network receive the user’s search and query requirements. For example, users can hardly find the detailed information they need by inputting a or several simple keywords.According to the above research background, this paper proposes a hierarchical model of related knowledge network based on semantic links. The hierarchical model can effectively organize the huge knowledge resources in the network and improve the query efficiency of the network while meeting the needs of different users. The research contents are as follows:First, we explore the ability of semantic differentiation between keywords in the related knowledge network. It is so important to research how to eliminate the barriers between the key words and human cognition in the network that users may search knowledge resources through keywords conveniently and efficiently. To solve this problem, we present the associated semantic link network model, which can divide the resources in the network into the topic layer, the text layer and the keyword layer.Second, the work study the basic characteristics of the key words in the related knowledge network. According to the active traction and passive traction keywords in the network, we analyze the main distribution of the four types of keywords. Based on the concept of the semantic similarity and the distribution law of the associated semantic links, the hierarchical model of the associated semantic links is proposed. The resources in the network are divided into three layers, namely, "the central meaning", "the main semantic" and "basic semantic".Third, this paper researches hierarchical model evaluation of semantic links in relational knowledge network. We verify the effectiveness of the hierarchical model from the split point and proves the rationality of the time complexity according to the evaluation algorithm of the model. Finally, the accuracy of the proposed layered model is verified according to the experimental data. According to the theory of the layered model, the reasonable application of the resources in the related knowledge network is achieved.In the face of the exponential growth of the different areas network resources, the hierarchical semantic links in the knowledge network provides a theoretical basis for the core topic of current interest in the field and the user’s intelligent browsing.